Autores
Shahiki Tash Moein
Ahani Zahra
Kolesnikova Olga
Sidorov Grigori
Título Analyzing Emotional Trends from X Platform Using SenticNet: A Comparative Analysis with Cryptocurrency Price
Tipo Revista
Sub-tipo JCR
Descripción Cognitive Computation
Resumen This study investigates the relationship between emotional trends derived from X platform data and the market dynamics of prominent cryptocurrencies—Cardano, Binance, Fantom, Matic, and Ripple—during the period from October 2022 to March 2023. Utilizing SenticNet, key emotions such as fear and anxiety, rage and anger, grief and sadness, delight and pleasantness, enthusiasm and eagerness, and delight and joy were identified. The emotional data and cryptocurrency price data, sourced bi-weekly, were analyzed to uncover significant correlations. The findings reveal that emotions such as delight and pleasantness and delight and joy have the strongest positive correlations with Fantom’s price, while delight and pleasantness exhibit the strongest negative correlations with Cardano and Binance. The study highlights the nuanced impact of specific emotional states on cryptocurrency prices, offering valuable insights for market participants. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Observaciones DOI 10.1007/s12559-024-10335-8
Lugar New York
País Estados Unidos
No. de páginas
Vol. / Cap. v. 2024
Inicio 2024-08-09
Fin
ISBN/ISSN